Investigating drilling characteristics of stir-squeeze cast Al6082 composites reinforced with MWCNTs DOI
Madhusudan Baghel, C. M. Krishna, Ashish Kumar

и другие.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science, Год журнала: 2024, Номер unknown

Опубликована: Июнь 13, 2024

Objective of current study is to examine the machining characteristics Al6082 composites embedded with multi-walled carbon nanotubes (MWCNTs). Herein, chemical vapor deposition (CVD) technique was used develop MWCNTs. Stir-squeeze casting method 0.3 wt.%−1.2 wt.% MWCNTs/Al6082 composites. Morphology MWCNTs analyzed by field emission scanning electron microscopy (FESEM). FESEM analysis performed for as-cast nanocomposites which showed uniform spreading up 0.9 and beyond that clusters were observed. Hardness tensile strength also measured observe impact addition reinforced highest hardness strength. It important drilling as CNT in tube form may become constraint if they are not uniformly distributed obstruct tool movement. CNC electric discharge (EDM) milling machine perform operation on varying cutting parameters. noticed inclusion enhanced material removal rate (MRR) surface finish owing brittleness. Strong interfacial bonding between matrix reduced delamination during operation.

Язык: Английский

Optimization and Comparative Analysis of Machining Performance of Al–Cu–SiC–GNP Composite: Influence of Reinforcement Variations Using Machine Learning, RSM, and ANOVA Validation DOI Open Access

Madduri Rajkumar Reddy,

Santhosh Kumar Gugulothu,

Talari Krishnaiah

и другие.

Advanced Engineering Materials, Год журнала: 2025, Номер unknown

Опубликована: Фев. 14, 2025

This study aims to optimize and analyze the machinability of Al–Cu–SiC–GNP composites using advanced techniques such as machine learning, (RSM), (ANOVA). The are fabricated an ex situ stir casting process with varying reinforcement percentages silicon carbide (SiC) graphene nanoplatelets (GNP) (2, 3, 5%), their is evaluated during water jet machining. key parameters analyzed material removal rate, surface roughness ( R a ), kerf width. Experimental findings reveal that significantly influence machinability. Optimal results achieved 5% SiC, 3% GNP, 300 MPa, 120 mm min −1 , balancing enhanced mechanical properties efficient ML models, including decision tree, random forest, support vector machine, artificial neural network (ANN), applied predict machining outcomes. Among these, ANN model exhibits highest predictive accuracy, capturing complex nonlinear interactions between input parameters. also validates through RSM ANOVA, confirming statistical significance on research provides robust framework for optimizing hybrid composite offers valuable insights into relationship content, parameters, performance outcomes, making it highly applicable aerospace automotive.

Язык: Английский

Процитировано

0

Investigating drilling characteristics of stir-squeeze cast Al6082 composites reinforced with MWCNTs DOI
Madhusudan Baghel, C. M. Krishna, Ashish Kumar

и другие.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science, Год журнала: 2024, Номер unknown

Опубликована: Июнь 13, 2024

Objective of current study is to examine the machining characteristics Al6082 composites embedded with multi-walled carbon nanotubes (MWCNTs). Herein, chemical vapor deposition (CVD) technique was used develop MWCNTs. Stir-squeeze casting method 0.3 wt.%−1.2 wt.% MWCNTs/Al6082 composites. Morphology MWCNTs analyzed by field emission scanning electron microscopy (FESEM). FESEM analysis performed for as-cast nanocomposites which showed uniform spreading up 0.9 and beyond that clusters were observed. Hardness tensile strength also measured observe impact addition reinforced highest hardness strength. It important drilling as CNT in tube form may become constraint if they are not uniformly distributed obstruct tool movement. CNC electric discharge (EDM) milling machine perform operation on varying cutting parameters. noticed inclusion enhanced material removal rate (MRR) surface finish owing brittleness. Strong interfacial bonding between matrix reduced delamination during operation.

Язык: Английский

Процитировано

2